GLM-5.2 vs GPT-5.3-Codex
GLM-5.2 (2026) and GPT-5.3-Codex (2026) compare a standalone API model against a coding-specialized model. GLM-5.2 ships a 1m-token context window, while GPT-5.3-Codex ships a 400k-token context window. On SWE-bench Pro, GLM-5.2 leads by 5.3 pts. On pricing, GLM-5.2 costs $1.40/1M input tokens versus $1.75/1M for the alternative. This page treats the result as workflow and deployment fit, not a universal model winner.
Treat this as a product-type comparison: GLM-5.2 is standalone API model, while GPT-5.3-Codex is coding-specialized model. Choose based on workflow fit before reading any benchmark or price row as decisive.
Decision scorecard
Local evidence first| Signal | GLM-5.2 | GPT-5.3-Codex |
|---|---|---|
| Product type | Standalone API model | Coding-specialized model |
| Best for | reasoning-heavy apps, tool-calling agents, and long-context analysis | custom coding agents, code generation, and tool loops |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 1m | 400k |
| Cheapest output | $4.40/1M tokens | $14/1M tokens |
| Provider routes | 1 tracked | 3 tracked |
| Shared benchmarks | SWE-bench Pro leader | 1 shared |
Decision tradeoffs
- GLM-5.2 holds a shared-benchmark lead on SWE-bench Pro, ahead by 5.3 points.
- GLM-5.2 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GLM-5.2 has the lower cheapest tracked output price at $4.40/1M tokens.
- Local decision data tags GLM-5.2 for Coding, RAG, and Agents.
- GPT-5.3-Codex has broader tracked provider coverage for fallback and procurement flexibility.
- GPT-5.3-Codex uniquely exposes Vision and Computer use in local model data.
- Local decision data tags GPT-5.3-Codex for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
GLM-5.2
$2,220
Cheapest tracked route/tier: OpenRouter
GPT-5.3-Codex
$4,900
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $2,680. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- GPT-5.3-Codex is $9.60/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- GPT-5.3-Codex adds Vision and Computer use in local capability data.
- Provider overlap exists on OpenRouter; start route-level A/B tests there.
- GLM-5.2 is $9.60/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision and Computer use before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-06-13 | 2026-02-05 |
| Context window | 1m | 400k |
| Parameters | 753B total, 40B active | — |
| Architecture | Mixture of Experts | Decoder Only |
| License | MIT(OSI) | Proprietary |
| Openness | Open source | Proprietary |
| Commercial use | Commercial use allowed | Commercial use with conditions |
| Knowledge cutoff | - | 2025-08 |
Pricing and availability
| Pricing attribute | GLM-5.2 | GPT-5.3-Codex |
|---|---|---|
| Input price | $1.40/1M tokens | $1.75/1M tokens |
| Output price | $4.40/1M tokens | $14/1M tokens |
| Providers |
Capabilities
| Capability | GLM-5.2 | GPT-5.3-Codex |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | No |
| Reasoning | Yes | Yes |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | Yes |
| Code execution | Yes | Yes |
| IDE integration | No | No |
| Computer use | No | Yes |
| Parallel agents | No | No |
Benchmarks
| Benchmark | GLM-5.2 | GPT-5.3-Codex |
|---|---|---|
| SWE-bench Pro | 62.1 | 56.8 |
Deep dive
On shared benchmark coverage, SWE-bench Pro has GLM-5.2 at 62.1 and GPT-5.3-Codex at 56.8, with GLM-5.2 ahead by 5.3 points. The largest visible gap is 5.3 points on SWE-bench Pro, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on vision: GPT-5.3-Codex. Both models share reasoning mode, function calling, tool use, and structured outputs, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, GLM-5.2 lists $1.40/1M input and $4.40/1M output tokens on the cheapest tracked provider, while GPT-5.3-Codex lists $1.75/1M input and $14/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts GLM-5.2 lower by about $3.13 per million blended tokens. Availability is 1 providers versus 3, so concentration risk also matters.
Choose GLM-5.2 when coding workflow support, larger context windows, and lower input-token cost are central to the workload. Choose GPT-5.3-Codex when coding workflow support and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, GLM-5.2 or GPT-5.3-Codex?
GLM-5.2 supports 1m tokens, while GPT-5.3-Codex supports 400k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is cheaper, GLM-5.2 or GPT-5.3-Codex?
GLM-5.2 is cheaper on tracked token pricing. GLM-5.2 costs $1.40/1M input and $4.40/1M output tokens. GPT-5.3-Codex costs $1.75/1M input and $14/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is GLM-5.2 or GPT-5.3-Codex open source?
GLM-5.2 is listed under MIT. GPT-5.3-Codex is listed under Proprietary. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for vision, GLM-5.2 or GPT-5.3-Codex?
GPT-5.3-Codex has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for reasoning mode, GLM-5.2 or GPT-5.3-Codex?
Both GLM-5.2 and GPT-5.3-Codex expose reasoning mode. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Where can I run GLM-5.2 and GPT-5.3-Codex?
GLM-5.2 is available on OpenRouter. GPT-5.3-Codex is available on OpenRouter, OpenAI API, and Vercel AI Gateway. Provider coverage can affect latency, region availability, compliance posture, and fallback options. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Continue comparing
Last reviewed: 2026-06-16. Data sourced from public model cards and provider documentation.